Paper Key : IRJ************939
Author: Mohammed Aleem Pasha
Date Published: 12 Apr 2025
Abstract
This research proposes a student assessment model that predicts Intelligence Quotient (IQ) using machine learning techniques. The model combines academic records, professor evaluations, and socio-economic factors to offer a holistic view of student potential and placement readiness. Data includes GPA, subject marks, problem-solving abilities, participation, parental education, and support systems. Quantitative reasoning and degree certifications were rated on a 110 scale. Multiple machine learning algorithms were trained and compared to identify the most accurate predictor of IQ levels (scaled 03) and salary expectations. The model aims to determine key factors influencing student placement and provide companies with a data-driven tool to enhance hiring while guiding students toward industry-aligned skill development .
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